EscoufierRV: Escoufier RV coefficient

In fruciano/GeometricMorphometricsMix: Miscellaneous functions useful for geometric morphometrics

Escoufier RV coefficient

Description

Computes the Escoufier RV coefficient

Usage

EscoufierRV(Block1, Block2)

Arguments

Block1, Block2

Matrices or data frames containing each block of variables (observations in rows, variables in columns).

Details

This function computes the usual version of the Escoufier RV coefficient (Escoufier, 1973), which quantifies the level of association between two multivariate blocks of variables. The function accepts two blocks of variables, either two data frames or two matrices each of n observations (specimens) as rows. The two blocks must have the same number of rows (specimens), but can have different number of columns (variables, such as landmark coordinates). The Escoufier RV has been shown (Fruciano et al. 2013) to be affected by sample size so comparisons of groups (e.g., species, populations) with different sample size should be avoided, unless steps are taken to account for this problem

Value

The function returns a number, corresponding to the Escoufier RV coefficient

References

Escoufier Y. 1973. Le Traitement des Variables Vectorielles. Biometrics 29:751-760.

Fruciano C, Franchini P, Meyer A. 2013. Resampling-Based Approaches to Study Variation in Morphological Modularity. PLoS ONE 8:e69376.

See Also

RVrarefied

Examples

library(MASS)
set.seed(123)
A=mvrnorm(100,mu=rep(0,100), Sigma=diag(100))
# Create a sample of 100 'individuals'
# as multivariate normal random data
# We will consider the first 20 columns as the first
# block of variables, and the following one as the second block

EscoufierRV(A[,1:20],A[,21:ncol(A)])
# Compute the EscoufierRV using the two blocks of variables

fruciano/GeometricMorphometricsMix documentation built on Jan. 31, 2024, 6:24 a.m.